High-throughput imaging platform

ABSTRACT

A microfluidic device capable of trapping contents in a manner suitable for high-throughput imaging is described herein. The microfluidic device may include one or more trapping devices, with each trapping device having a plurality of trapping channels. The trapping channels may be configured to receive contents via an inlet channel that connects a sample reservoir to the trapping channels via fluid communication. The trapping channels are shaped such that contents within the trapping channels are positioned for optimal imaging purposes. The trapping channels are also connect to at least one exit channel via fluid communication. The fluid, and contents within the fluid, may be controlled via hydraulic pressure.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to and benefit of U.S. ProvisionalPatent Application Ser. No. 62/068,822 filed Oct. 27, 2014, which isfully incorporated by reference herein and made a part hereof.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government Support under Grant Nos.#R01AG041135 and #R01NS060129 awarded by the National Institutes ofHealth. The Government has certain rights in the invention.

BACKGROUND

Drug discoveries require methodologies to screen new compounds in smallquantities using model systems in a high-throughput manner. Screeningcompounds in model systems are necessary to obtain new hits before thecompounds are taken for clinical or human trials. The two types of modelsystems are in vitro (performed with cells or biological moleculesoutside their normal biological context) and in vivo (performed onwhole, living organisms) model systems. Whole organism in vivo modelsare far better than the 2D/3D in vitro systems that use cell lines,accounting for more factors and providing more accurate results.

Traditionally, high-throughput drug screens are based on in vitro cellcultures which do not delineate all the aspect of in vivo testing suchas drug absorption, circulation, metabolism, excretion, and toxicity asfound in humans. Use of in vitro model in drug discoveries hasencountered with poor hit-to-lead rates and clinical translation. On theother hand, traditional in vivo testing models have been eitherlow-throughput or low resolution, hindering the testing process.

Typically, in vivo models are conducted on basic organisms such as C.elegans, C. brigsae, and plenaria. The C. elegans is particularly wellsuited to in vivo models due to its short life span, well characterizedgenetics, simple neuronal circuit, small number of cellulararchitecture, and amenable worm body throughout its development. The C.elegans genome share approximately 65% homology with human disease genesand has been an attractive platform for elucidating disease pathways.Because of its faster life cycle and smaller genome size, C. elegansprovides a useful tool for genetic manipulation. New disease models havebeen demonstrated using C. elegans for neurological diseases, geneticdisorder, cancer, and developmental disorder etc.

The typical testing methods for worms such as C. elegans includesplacing the worms in the wells of a multi-well plate and analyzing themusing anesthetic solution. However, the worms in the wells are notaligned or organized properly using this method. For example, in highdensity fluid the worms can settle at the bottom of the well and stackup on top of each other. On the other hand, in low density fluid theworms are better isolated but require more imaging data in order toproduce sufficient data for statistical analysis. In light of thedrawbacks of current methods, there exists a need for a high-throughputimaging system for accurate, high quality, and high speed in vivoscreening of organisms such as C. elegans.

Other systems, methods, features and/or advantages will be or may becomeapparent to one with skill in the art upon examination of the followingdrawings and detailed description. It is intended that all suchadditional systems, methods, features and/or advantages be includedwithin this description and be protected by the accompanying claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The following detailed description will be better understood when readin conjunction with the appended drawings, in which there is shown oneor more of the multiple embodiments of the present invention. It shouldbe understood, however, that the various embodiments of the presentinvention are not limited to the precise arrangements andinstrumentalities shown in the drawings.

FIG. 1 is a cross-sectional view of an example embodiment of amicrofluidic device.

FIG. 2 is an example embodiment of a trapping device having multipletrapping channels.

FIG. 3 is a graph showing pressure cycles for an example embodiment.

FIG. 4 is a graph for an example embodiment illustrating aspect ratioversus channel length and channel height versus channel length.

FIG. 5 is an example embodiment of a microfluidic device having aplurality of trapping devices.

FIG. 6 shows flow charts for three steps in the process of analyzingimages in an example embodiment.

FIG. 7 is an example embodiment of an imaging system including amicrofluidic device and a computer.

FIGS. 8A to 8H show automated image analysis to estimate the blobparameters using multiple z-stack images.

DETAILED DESCRIPTION

A microfluidic device capable of trapping contents in a manner suitablefor high-throughput imaging is described herein. The microfluidic devicemay include one or more trapping devices, while each trapping device mayhave a plurality of trapping channels. The trapping channels may beconfigured to receive contents via an inlet channel that connects asample reservoir to the trapping channels via fluid communication. Thetrapping channels are shaped such that contents within the trappingchannels are positioned for optimal imaging purposes. The trappingchannels are also connected to at least one exit channel via fluidcommunication. The fluid, and contents within the fluid, may becontrolled via hydraulic pressure.

An example microfluidic device is shown in FIG. 1. The device shown inFIG. 1 includes a substrate 110 upon which a trapping channel 120 isbuilt. Substrate 110 may comprise any suitable material for building atrapping channel upon. For example, substrate 110 may be glass, metal,plastic, or any other suitable material. Trapping channel 120 may beformed via a void in material 130. Material 130 may include any suitablematerial for forming trapping channel 120, such as, for example,polydimethylsiloxane. Any other material capable of being formed into anappropriate shape may also be used. Material 130 may also include aninlet 160 and an exit 170 to allow fluid to flow through trappingchannel 120.

FIG. 1 also shows top gasket 140 and bottom gasket 150, which may beincorporated into the microfluidic device in order to influence fluiddynamics of the fluid used with the device. For example, top gasket 140may include channels for coupling trapping channel 120 to other fluidpathways. Top gasket 140 may also include a passageway for releasing airor other gasses trapped within the fluid in the system. Bottom gasket150 may be used to seal the bottom portion of the device and preventfluid leaks while maintaining appropriate pressure levels. Screws 180may be utilized to secure the substrate 110, trapping channel 120,material 130, top gasket 140, and/or bottom gasket 150.

FIG. 2 shows an example embodiment of a trapping device having multipletrapping channels. In this embodiment, the trapping device includes fivetrapping channels 220. The trapping channels 220 may receive fluid viainlet channel 260, which in turn may receive fluid via reservoir 230.Reservoir 230 may be filled with fluid via a well (not shown) or anyother suitable method. In the example embodiment of FIG. 2, the fluidcontains subjects 240. Subjects 240 may be any suitable subject fortesting, including animals. For example, subjects 240 may be C. elegans,a small worm commonly used for testing pharmaceutical products in vivo.Trapping channels 220 may also be connected to exit channel 270 viafluid communication, such that the imaged subjects 240 and associatedfluid exits through exit channel 270. The term “fluid communication” isused broadly to mean that fluid flow is possible between two locations.Fluid communication does not require consistent fluid flow, but ratherthe ability to transport fluid from a first location to another.

FIG. 2 also includes cross-sectional views of a trapping channel 220 atdifferent points along its length. Cross section 290, labeled “free,” isa cross-sectional view of trapping channel 220 at a first section of thechannel. Cross section 280, labeled “trap,” is a cross-sectional view oftrapping channel 220 at a second section of the channel. A “section” ofa channel may comprise a measurable length of the channel, or maycomprise an infinitesimal portion of the channel. A comparison of thesetwo cross sections makes it clear that cross section 280 is smaller inat least one dimension relative to cross section 290. In thisembodiment, the cross section size of cross section 280 may cause thepoint of interest 250 to align in a particular way.

In an example embodiment, point of interest 250 represents the ventralside of subject 240, particularly a C. elegans organism. The shape oftrapping channel 220 may be varied to orient point of interest 250 in aparticular direction. In this manner each trapping channel 220 may trapand orient subjects 240 in similar orientations. This orientation aidsin image capture, as the image can be captured from the ideal directionin a repeatable manner. Point of interest 250 may represent differentportions of the C. elegans or may relate to a different organismentirely. While C. elegans are discussed herein, the subject matter ofthis application is not limited to this particular type of organism.

Trapping channel 220 may have a height and width, measured relative to asupport surface such as substrate 110 in FIG. 1. In one embodiment,trapping channel 220 is aligned such that its length is parallel to thesurface of the substrate. The “height” of trapping channel 220 cantherefore be measured in a direction perpendicular to the surface of thesubstrate. The “width” of trapping channel 220 can be measured in adirection parallel to the surface of the substrate but perpendicular tothe axial direction along the length of trapping channel 220.

In one embodiment, the height of trapping channel 220 is varied along ata plurality of locations along the length of the channel. For example,the heights of at least two of the sections of trapping channel 220 maydiffer from one another. In another example, the height of trappingchannel 220 is varied continuously along at least a portion of thelength of the channel. In one example, the variations in height areprovided such that the height of trapping channel 220 decreases in thedirection of flow—i.e from the inlet channel side to the exit channelside of the trapping channels.

The particular dimensions of the microfluidic device can vary based onimplementation. In one example embodiment, however, inlet channel 260comprises a height of about 1 μm to about 500 μm and a width of about 1μm to about 750 μm. In another example embodiment, the length oftrapping channel is about 200 μm to about 6 mm.

In order to control the flow of fluid through the microfluidic device,pressure regulation may be used. Any suitable method for controllingpressure may be used. FIG. 3 shows a graph of an example pressureregulation cycle that may be used. The graph in FIG. 3 shows that thepressure is cycled between “ON” and “OFF” states in a cyclical manner.Any appropriate pressure levels may be used, and should be matched tothe size of the microfluidic device, trapping channels, and subjectsbeing tested. In one example embodiment, the pressure is cycled betweenabout 0 and 30 psi. Similarly, the time period for the cycles may betailored to the particular device. In one example embodiment, eachpressure cycle is maintained for a time period of 0 to 600 seconds.

FIG. 4 is a graph for an example embodiment illustrating aspect ratioversus channel length and channel height versus channel length. The axisalong the left side of the graph is channel length, measures inmillimeters, and ranges from 0.0 to 3.0. Along the top of the graph isaspect ratio, measured as width divided by height. The aspect ratio isillustrated by the line that roughly follows the dotted line. In thisembodiment, the aspect ratio varies from about 0.4 to about 1.2. In someembodiments, the aspect ratio remains within a range of about 0.2 toabout 2.0. Along the bottom of the graph is channel height, measured inmicrometers. The line on the right represents channel height, and rangedfrom about 50 to about 100 μm in this particular embodiment. In otherembodiments, the height may range from about 1 μm to about 500 μm alongthe length of the trapping channel.

FIG. 5 is an example embodiment of a microfluidic device having aplurality of trapping devices. In this example embodiment, themicrofluidic device labeled as “(A)” contains 96 individual trappingdevices. In other embodiments, however, any number of trapping devicesmay be used. A subset 520 of trapping devices is labeled as “(B).” Thesubset 520 of trapping devices includes an intermediate exit channel530. Each of the eight trapping devices in subset 520 have an individualexit channel in fluid communication with intermediate exit channel 530.In one embodiment, the trapping devices have different size exitchannels in order to equalize pressure among the various trappingdevices. For example, the trapping devices labeled D11 and D12 in subset520 have larger exit channels than the trapping devices labeled A11 andA12. In this embodiment, A11 and A12 are closer to the exit point ofintermediate exit channel 530, and therefore smaller exit channels cansuffice. On the other hand, D11 and D12 are farther from the exit pointof intermediate exit channel 530, and therefore larger exit channels arenecessary.

The intermediate exit channels 530 from each subset of trapping devicesmay join in fluid communication a final exit channel 540. Themicrofluidic device labeled (A) in FIG. 5 shows two final exit channels540 on opposite sides of the device. The final exit channels 540 may beformed by a gasket surrounding the microfluidic device. The exitchannels 270, intermediate exit channels 530, and final exit channels540 may be configured such that the hydraulic resistance experience byeach trapping device is similar across all applicable trapping devices.

In order to provide the fluid and subjects for testing to themicrofluidic device, the fluid and subjects may be deposited in thereservoirs 230 of one or more trapping devices. In an exemplaryembodiment, wells 510 are used to control the deposition of this subjectmatter to the reservoirs 230. In FIG. 5, the trapping device labeled“(C)” shows a dotted line for well 510 because the well is positionedabove the plane of the trapping device. Well 510 may be a funnel,syringe, hose, tube, or any other device for providing fluid andsubjects for testing. In one embodiment, well 510 is a substantiallyfrustoconical shape with the smaller end of the shape proximate thereservoir 230.

The microfluidic device described in various example embodiments abovemay be incorporated into a high-throughput imaging system. In oneexample embodiment, the imaging system includes a microfluidic device, apressure device connected to the microfluidic device via a fluidicconnection, a microscope with a camera and a motorized platform, and aprocessor. In one embodiment, the motorized platform is configured tosupport the microfluidic device such that any changes in the location ofthe motorized platform also moves the microfluidic device. In otherembodiments, the motorized platform may move the camera or other imagingequipment used in conjunction with the camera. Regardless of theimplementation, the motorized platform may be capable of moving in threedimensions.

In one embodiment, the process comprises computer-readable instructionsfor applying hydraulic pressure to the microfluidic device, moving themotorized platform such that the camera captures the contents of themicrofluidic device, capturing the contents of the microfluidic deviceas image files, and saving and storing the image files to a storagedevice.

The imaging system may also be capable of calculating and adjusting forvarious imperfections in the system. For example, the system may becapable of calculating offsets in a focusing plane of the contents inthe trapping devices. These offsets may be caused by, for example,imperfections in the manufacturing process of the devices. Similarly,the system may be able to calculate a curvature of the substrate usedfor the microfluidic device. The substrate may undergo curving due tothe hydraulic pressure used within the trapping devices. The system cantherefore measure or calculate the curvature based on the pressureand/or measurements at locations of the substrate. This may includeobtaining x, y, and z coordinates of a plurality of predeterminedlocations of the microfluidic device. The system may then move themotorized platform and/or adjust the camera settings to compensate forthe factors described above.

An image analyzer may also be used in conjunction with the imagingsystem. In one embodiment, the imager analyzer receives stored imagesfor analysis. The analyzer can identify the trapping channels and thedesired contents of the trapping channels, and crop the image to removethe portions of the trapping channels that do not have the desiredcontents. The analyzer is also capable of comparing a plurality ofimages of the desired contents at different focal planes. The images atdifferent focal planes may be considered different images in the imagestack, or z-stack. The analyzer can select the most desirable image inthe stack and display a version of that image on a graphical userinterface.

In one embodiment, the display settings of the images on the graphicaluser interface can be adjusted in real time to aid in scoringphenotypes. In another embodiment, a particle size filter can be used toremove all foreign particles in the area of interest on the graphicaluser interface. In some embodiments, the image analyzer is automated andcan select focal planes and score phenotypes automatically.

FIG. 6 discloses flow charts describing an example embodiment of animage analysis for neuronal health assessment of C. elegans organisms.Each flow chart describes a particular task, such as locating the worms,finding the plane of best focus, and scoring neurons in the worms.

With respect to locating worms in the channels, block 610 initiates theprocess of loading an image stack. At block 612 the stacks are summed.At block 614 the images are smoothed according to a smoothing process.At block 616 the system obtains a normalized intensity profile acrosschannels. And at block 618 the worms are located from intensity peaks.Next, at block 620 the images of individual worms are cropped and atblock 22 the worm body is located via a binary threshold. At block 624unwanted objects are removed via particle filtering. Block 625 querieswhether the worm is fully in the field of vision. If not, then at block626 the centroid of the worm is predicted. If so, then the centroid ofthe worm is located at block 627. At block 628, the plane of best focusfor the feature of interest is located. Finally, the neurons are scoredfor the worm. At block 630 the cropped, filtered images are loaded. Atblock 632 the neurons of interest are manually scored—although in otherembodiments this step is completed automatically. At block 634 an outputplot is generated and may be displayed on a graphical user interface.

FIG. 7 is an example embodiment of an imaging system including amicrofluidic device and a computer. The microfluidic device 710 isenclosed within an upper gasket 712 and a lower gasket 714. The device710 and gaskets 712 and 714 may be operably connected to platform 716.Platform 716 may be a motorized platform that is controlled by acomputer 726. The computer 726 also controls a valve 718 which can beused to influence the hydraulic pressure applied to device 710. FIG. 7also shows a camera 720 used in conjunction with a mirror 722 and aobjective 724. The computer 726 also includes a monitor 728 or othergraphical user interface. The interface may be used to display results730 of the imaging.

Example—Fabrication of the Microfluidic Device

The following description is merely one example of the fabrication of amicrofluidic device. Microfluidic devices were fabricated usingthree-layer photo-lithography and single-layer soft-lithographytechniques. In brief, we designed photo masks using AutoCAD 2013 andprinted them on transparencies using 50K DPI resolution laser-plotter(Fineline Imaging). A 6 inch silicon wafer was spin coated with SU8-2025photoresist (Microchem Corp.) at 2100 rotation per min (rpm) to obtain aheight of ˜45 μm (Layer-1, red). The layer was exposed to UV light usinga photo-mask with the pattern for layer-1. The layer was developed andcoated with the second layer of SU8-2025 at 1900 rpm for 33 sec toobtain a height of ˜65 μm. The second layer was exposed to UV using aphoto-mask with the pattern for layer-2. The layer was developed andcoated with the third layer of Su8-2035 photoresist (Microchem Corp.) at1650 rpm for 33 sec to obtain a height of ˜85 μm. The third layer wasexposed with a photo-mask with the pattern for layer-3. The SU8 moldwith all three layers was treated withtridecafluoro-1,1,2,2-tetrahydrooctyl-1-trichlorosilane vapor (UnitedChemical Technologies) in a vacuum chamber at 40° C. to reduce surfaceadhesion during soft-lithography process.

Polydimethylsiloxane (PDMS, Dow Corning) was mixed in the ratio 10:1 andpoured on the silanized SU8 mold with a 96-well PCR plate positioned ontop of the SU8 features such that every well was aligned and placed ontop of the circular pad at the entrance of every parallel immobilizationdesign. The PCR plate was pre coated with silane vapor in vacuum chamberto ease its release after PDMS curing. An acrylic holder was placed onthe silicon substrate with SU8 features to restrict outer dimension ofthe PDMS mold and achieve a height of around 8 mm of PDMS. PDMS layerwas cured at 70° C. for 2 hours, peeled off from the SU8 mold, andreleased from the PCR plate. The PDMS block was punched for 12 exits andbottom of all 96 wells using a hydraulic punch (Syneo). The PDMS blockwas cleaned and bonded to a 3/16 inches borosilicate glass substrateusing 100 W oxygen plasma. The device was finally cured at 70° C. for 6hours for complete sealing.

Example—Gasket and Pressure System

The following description is merely one example relating to the subjectmatter discussed in this application. The gasket system comprised of anacrylic (Gasket-1) and an aluminum (Gasket-2) piece. An acrylic sheet of¼ inches thickness was machined for gasket-1 with one buffer entry portand one air vent. A volume of 4.4 inches×3.0 inches×⅛ inches was milledout at the center of gasket-1 to hold sufficient buffer volume on top ofall 96 wells embedded in the PDMS block. Two narrow lines were milledalong the edge of larger sides of the rectangle to connect all 6 exitpunches on each side of the PDMS block. Both exit channels in gasket-1were connected to an external waste reservoir using a luer connector andfitted with a flexible tube. The size of gasket-2 was machined to matchthe flat-top motorized stage. Most of the material in gasket-2 wasremoved from central area to reduce material weight and enablefluorescence imaging from an inverted microscope. A thin step ingasket-2 matched the foot print of the glass substrate of PDMS devices.The top and the bottom gasket (gasket-1 and gasket-2) pieces were heldtight using six screws to avoid buffer leakage during high pressuresteps. The device was operated using filtered M9 from a 500 mL reservoirthat was pressurized using compressed air. The pressure was transmittedto gasket-1 through a computer controlled solenoid valve.

Example—Automated Image Acquisition

The following description is merely one example relating to the subjectmatter discussed in this application. Bright field and fluorescentimages were acquired using an Olympus IX73 microscope equipped with a 4megapixel, 7.4 μm×7.4 μm pixel size, 15 frames per second maximum framerates, CCD camera (MegaPlus ES4020, Princeton Instruments). Bright fieldand fluorescence images were acquired using a 2× (0.06 NA) and 10× (0.3NA) objectives respectively using an in-house labVIEW program. Thesoftware controlled the movement of a motorized platform equipped with a114 mm×75 mm (±44 nm resolution) flat-top XY translational stage, and a500±0.002 μm traveling range piezo stage (MS2000, Applied ScientificInstrumentation). The scan area and translation commands were optimizedfor whole 96-well device design with 40 immobilization channels perwell. In addition to the imaging routine for immobilization channels,the program detected alignment markers embedded on the PDMS block toquantify and compensate for offset values in all three axes duringdevice imaging. The program integrated user defined parameters such asarray size, number of image stacks, strain information in each well, andchemicals used in each well into the automated acquisition loop.Automated acquisition sub-routine acquired image stacks at everylocation and saved each frame by annotating them with an appropriatefile name generated by the program. A full chip with 96-well devicegenerated ˜40 GB of images and stored them in the form of 16-bit imagesfrom the 4 megapixels CCD camera.

Example—Semi-Automated Image Analysis

The following description is merely one example relating to the subjectmatter discussed in this application. We developed an in-house graphicaluser interface (GUI) that allowed user to load saved image stacks atspecific locations of the device from a specific screening experiment.All image stacks were loaded from a particular location of the chip andsummed up to increase the contrast between the neurons and surroundingareas. The summed image was processed with a Gaussian low pass filter(σ=1.0) to attenuate high frequency features. The filtered image wasprojected on one side of the device and normalized to remove anybackground fluctuation due to non-uniform illumination. The algorithmsearched for peaks above a threshold of 5×10⁴ and separated by at least150 pixels. Worms in a trap corresponded to large peak in theprojection. An area of 2048 pixels×200 pixels centered at a peak wascropped to isolate single worms immobilized inside the microfluidicchannel. Cropped worm image was thresholded so that 15% of pixels areabove the threshold and converted to a binary image. A size filteringwas used to remove all foreign particles smaller than 5000 pixels inarea leaving only worm body in the field of view. Centroid of the wormbody was either selected or predicted from the edge of the wormboundary. A smaller window of 201 pixels×201 pixels were selected aroundthe worm centroid and analyzed for neuronal fluorescence. Assuming thebrightest signal was from the neuron when it was in focus we searchedfor the brightest spot in the whole ROI through all the image stacks.The whole worm corresponding to the same focal plane was displayed tothe user for scoring. In our C. elegans AD model study, VC4 and VC5neurons were scored as ‘Normal’ or ‘Degenerated’ or ‘Do Not Score’ ifthey were ‘healthy’ or ‘dim/missing’ or ‘not in focus’ respectively. Thewhole worm was assigned with an additional remark for ‘Dim Worm’,‘Neurons Misshapen’, and ‘Axon Beading’ if the worm was out of focus,VC4/VC5 cell bodies were misshapen, and neuronal process were beaded.Scoring options were displayed on the screen to be selected for eachworm and the scores were saved in multi-dimensional array to beextracted for statistical analysis. The scores could be opened at laterpoint for future references and review process along with the images.

Example—C. elegans Strain and Maintenance

The following description is merely one example relating to the subjectmatter discussed in this application. C. elegans were grown andmaintained on nematode growth medium (NGM) agar plates with HB101bacteria at 20° C. We used following C. elegans strains in this work:LX959 vsIs13 (lin-11::pes-10::GFP+lin-15 (+)), JPS67 vsIs38; unc-119;vsIs13; lin-15B, CZ1200 juIs76 (unc-25p::GFP+lin-15(+)), AM138 rmIs130(unc-54p::Q24::YFP), AM140 rmIs132 (unc-54p::Q35::YFP). C. elegansstrains LX959 and JPS67 were considered as wild type and APP mutant forneuronal degeneration studies in this work. In both strains all six VCneurons were marked with green fluorescent proteins (GFP) that can bevisualized under fluorescent microscope. The AM138 and AM140 strainshave 24 and 35 subunits of polyglutamine (PolyQ) labelled with YFPfluorescent protein in their body wall muscle cells.

C. elegans strains were maintained and synchronized at 20° C. for largepopulation of liquid culture worms for high throughput studies indevices. Four healthy larval stage 4 (L4) hermaphrodite were transferredto a 10 cm diameter NGM plate containing HB101 bacterial lawn at 20° C.The plate would produce ˜900-1000 gravid worms in 7 days which is thenbleached to obtain 6000 viable eggs on bleaching. The bleached eggs wereincubated at 20° C. in a 360 degree rotor for 24 hours for all the eggsto hatch and obtain age synchronized larval stage 1 (L1). Hatched L1swere cleaned by filtering hatched worms through a 20 μm filter thatseparated healthy L1s from unhatched eggs, unhealthy/dead L1s, and wormcarcasses present in the liquid. Healthy L1s were collected in a glasstube and centrifuged at 1000 rpm for 2 min to achieve a worm density of˜100 worms/10 μL of liquid. A volume of 20 μL was dispensed in 32 wellsof 24-well plates with an additional 1 mL of HB101 bacterial food in S.medium (1×10⁹ cells/mL). The worms were incubated at 20° C. and shook at80 rotation per min (rpm) for 48 hours till they reach late L4 stage.Well plate was left on a horizontal surface for 10 min for the worms tosink down to the bottom of the well. 1 mL of freshly suspended HB101 wasadded in every well. 50 μL of FUdR (8.4 mM in water) was added to everywell to avoid production of new young worms in the well volumes.Appropriate drug compounds were added in designated wells at knownconcentrations. The plates were incubated for 72 hours till the wormgrew to day 3 adult (D3) stage. Each well of the 32 wells were dispensedto three wells on a 96 well plates with a 40 μm filter sieve. Worms werefiltered, rinsed, and transferred to a fresh 96-well collection plate.Worms were pipetted from individual wells to the wells of a primeddevice to be used for imaging using high-throughput screening platform.

Example—Channel Geometry

The following description is merely one example relating to the subjectmatter discussed in this application. Total assay time is an importantparameter and can be a bottle neck in high throughput studies. Byreducing experimental time per run one can screen more number ofcompounds/populations that increases the possibility of finding newcandidates in a chemical/genetic screen. We engineered a parallelarchitecture to immobilize a maximum of 3840 worms in a 96-well devicewith 40 channels per well to reduce the assay time for C. elegansscreening platforms. The whole device is operated under a common gasketsystem and requires design optimization to achieve identical flow rates.The 96-well device is divided into smaller batches of 8-well sectionsconnected together to common exit port. Both pairs of 6 exit ports (E₁and E₂) on the two sides of the PDMS block align with the common exitgrooves in the top-gasket on two sides. Worm entrances and exit channelsare fabricated with largest thickness (85 μm) to avoid physical stresson worms inside the device during loading and reduce total hydraulicresistance. Worm motion gets reduced as they are pushed inside thedevice with multiple immobilization cycles and its relative positioninside the device with lower channel widths of 65 μm (green) and 45 μm(red). The width of the channel is varied along the length to achieveaspect ratio (channel height to channel width) values within 1.2-0.4.Day 3 adult worms growing in liquid culture are immobilized in theregion with ˜1.0 aspect ratio. Every well is connected to the main flushoutlet through an exit channel. A positive pressure gradient across thechannel helps to load worms inside the channel and keep them in positionduring z-stack imaging.

Large dimension of the device demands special design layout andintelligent wiring of the exit channels to be able to achieve similarflow rates, faster loading, and identical worm immobilization within 40traps of a well and amongst all 96 wells. Flow rates depend on thehydraulic resistances which is a function of the geometrical shape ofthe microfluidic channel. Since primary contributor to the hydraulicresistance is exit channel length, flow rate decreases with the relativeposition of the well with respect to the outlet punch. Devicefabrication and operation requires minimum number of exit punches on thedevice boundaries out of the well region. We designed a symmetric96-well device with two rows of 6 exits on top and bottom of the device.Each exit connects 2×4 wells with four different exit channel lengths.Well A01 situated on first row and closest to the exit presents minimumtotal hydraulic resistance and maximum flow rates. Flow rate reduces by˜50% for well D01 which is farthest from the exit. The variation in theflow rates are more prominent at higher well pressure. To reduce theeffect of well location on flow rates hydraulic resistances are requiredto be modulated by compensating channel lengths with altered channelwidths.

Example—Automated Image Acquisition

The following description is merely one example relating to the subjectmatter discussed in this application. In manual screening worms aremounted on agar pads and can be randomly positioned and oriented withrespect to each other. This immobilization method requires additionalamount of time and multiple field of views to screen every worm withhigh enough resolution. Labor intensive steps and long analysis timelimit manual phenotypic screens to a few populations. Using ourmicrofluidic immobilization device one can immobilize 4000 worms inparallel in a 96-well device format. Worms are loaded in 96-well deviceand clamped in between the gasket system before they are immobilizedinside the trapping channels using an on/off pressure cycle. The deviceis mounted on a flat-top motorized XY stage and equipped with a 500 μmpiezo. All 3-axis motions are controlled using an in-house labVIEWalgorithm. The automation program has two main steps 1) wormimmobilization, and 2) adaptive device scan with input parameters.

All 96 wells are filled with approximately 60 D3 adult worms in M9buffer and clamped between the gasket systems to avoid pressure leakageduring immobilization cycle. Top gasket is filled slowly with M9 bufferunder 0.5 psi pressure and an open air vent. Slower filling rate avoidsworm mixing between wells due to spill over during buffer flow. The airvent and both exits (E₁ and E₂) are closed immediately after the bufferis filled in the top gasket. Worms are able to swim freely at the wellbottom and around the channel entrances. Worms are immobilized using anon-off cycle and under 4 psi pressure on the 96-well gasket system.Exits E₁ and E₂ are opened simultaneously on both sides to immobilizeworms in all 96 wells simultaneously. The whole 96-well immobilizationis achieved in less than 5 min and dispenses about 100 mL of buffervolume. One of the well from D01-E12 is viewed with low magnification(2×, 0.06 NA) to monitor extent of immobilization with cycle number.Once the immobilization cycle is complete the stage is manually moved torecord XYZ coordinates of wells A01, A12, H01, and H12 using 10×, 0.3 NAobjective to calibrate XY offset (θ) and XZ tilt (δxz and δyz) of thechannel design with respect to the stage axes. The values are calculatedfor every position on the device and corrected for respective axesduring imaging steps.

Example—Automated Image Analysis of C. elegans Disease Model

Manual image analysis of subtle phenotypical changes in such large-scalescreens is another bottleneck that limits the overall speed of theassay. In order to demonstrate a full-automated data acquisition andanalysis of high resolution fluorescence image stacks a proteinaggregation disease model strain was used. The model, AM140 strain, has35 ployQ chains in body wall muscles that shows age dependentaggregation. The control worms, AM138 strain, with shorter size of PolyQfragments does not have such aggregation phenotypes at similar ages. Toreduce the time required for image analysis and simplify the datahandling process for large-scale, 3D stacks of images collected withthis HTS system, a fully automated image analysis GUI was developed(FIG. 8A). The GUI aligns all four field-of-views and identifieschannels with an immobilized animal corresponding to the peaks in theprojected intensity profile (FIG. 8B, 8C). The algorithm extracts eachanimal at the best focus plane for image processing (FIG. 8D) andidentifies the aggregates on the best-focal image for each animal (FIG.8E). Phenotypical scores for each animal are saved automatically in amulti-dimensional array. Using this GUI, it was then possible to analyzeall collected images from the whole 96-well chip for aggregationstatistics of the trapped animals in approximately 15 min (FIG. 8F).This automated image analysis successfully reduced the data processingtime by at least two orders of magnitude compared to all the automatedsteps of the GUI when performed manually. The phenotypical scoresregistered in the GUI for a whole 96-well experiment are exported into ascattered plot (FIG. 8G). Blob parameter shows a clear separation whichyields a high Z′-factor of at least 0.80 for our screen platform withthis model. Combining multiple wells can lower the variance leading toimproved Z′-factor of the screen (FIG. 8H).

Example—384-Well Device for L4 Stage Animals

The following description is merely one example relating to the subjectmatter discussed in this application. We have designed and optimized a384-well parallel immobilization device for super high-throughputimmobilization and imaging of L4 stage C. elegans. In a similar fashionto the 96-well platform, each well leads to a microfluidic device. Eachdevice is designed to orient and immobilize 30 L4 stage worms, for atotal of 11,520 worms. Similar to the 96-well design, each set of 4×2devices on one half of the platform are connected in series to an exitport. In order to optimize the resistances and achieve nearly equal flowrate, a staggered exit channel layout is designed. This staggered designconnects 4×2 wells and overlaps with another 4×2 wells, creating roughlytwice as many exit channels. Using this layout, the geometries of theexits arms have been optimized to achieve nearly identical aspect ratioand equal flow rates. This 384-well platform can be run with the samegasket setup as the 96-well platform. This system enable high-throughputoptical interrogation of L4 stage C. elegans for large-scale imagingbased studies that require large population sizes for phenotyping. Sincethe device interface is formatted for the standard 384-well platform,the technology can be a great value for commercial research labs andlarge scale high-throughput screening for C. elegans.

Example—Success of Exemplary Device

The following description is merely one example relating to the subjectmatter discussed in this application. A microfluidic based technologyhas been demonstrated that has single pressure input, no 3D valvecontrol, 30 min pre-conditioning, parallel sample handling, adapted formulti-well plate handling, and an easy protocol for non-technologists.The device has twelve segments of 8-well platforms and can be fabricatedas different sets of multiple of 8-well configurations. The devicerequires one ˜5 psi pressure line and dispenses ˜100 mL of buffer to runthe whole chip with an appropriate gasket design. Users can select anyrectangular size well array on the chip to scan predefined well numbers.All 96 wells with 40 immobilization channels per population immobilizemaximum 3840 worms in less than 5 min. An on/off immobilization cyclepushes the worm inside a tapered channel geometry with varying aspectratio, orienting ˜4000 worms simultaneously in lateral direction. Wecaptured all 40 channels per population in a whole 96-well device inless than 12 min using 10× objective (0.3 NA) and a large size camera.Worms immobilized inside the channel encounters higher level of stresscausing increased autofluorescence thus reducing the sensitivity of thescreen (poor signal to background ratio). We found similar level ofbackground fluorescence in our microfluidic device. Hence, shorterimmobilization and imaging time is very advantageous for C. elegansscreens with weaker expression level of fluorescent reporters.

One full chip scan generates 4608 images from 3840 worms. The chip iscapable for high resolution imaging screens with higher numericalaperture objectives and capture more z-stacks per location. A higher NAobjectives with smaller field of view would require increase number ofimaging locations to cover the whole length and all 40 channels. Sinceour immobilization cycle has nearly no head-tail orientation bias, onecan capture all 40 channels with higher resolution and smaller field ofview to acquire the signal from ˜50% population with head or tailportion of the body. LabVIEW acquisition algorithm annotates data withall information and saves them in a folder. We developed a GUI toanalyze fluorescence signals semi-automatically for neuronal phenotypes.The GUI loads all images from a user defined well population anddisplays single worm image stacks at a time to be inspected visuallybefore scoring them for neuronal health. We scored all 3840 channelsfrom a whole 96-well chip and saved them in a 9-dimensional array inapproximately 8 hours. All the scores are pooled together from themulti-dimensional array and displayed for statistical tests. In anattempt to demonstrate the capability of the high-throughput system, wedeveloped a fully automated image analysis for C. elegans Huntington'smodel with degenerating body wall muscles. The worms are imaged usingsimilar image acquisition algorithm and can be analyzed for degenerationphenotype from the whole 96-well device in less than 15 min.

This screening platform can easily be adapted by a research laboratoryfor imaging based studies that require large population sizephenotyping. Since the device interface is formatted for standard96-well device, the technology can be a great value for commercialinfrastructure for large scale high-throughput screening for C. elegans.An automated image processing algorithm that focuses on a specificneurodegenerative disease model may be able to analyze the complete datain less than 30 minutes. Even though we have used D3 stage C. elegans inour screen, one can use the same design principle for different stage ofthe worm with altered device dimension to achieve similar efficiency ofimmobilization. A younger stage worm would require smaller devicedimension which can allow expansion of the 96-well format to larger wellformats.

The subject matter described above may be carried out via a computersystem for realization of a computer-implemented apparatus that may formall or a portion of one or more implementations or embodiments of thepresent disclosure. The computer system may include a computer, akeyboard, a mouse, and a display device (e.g., computer monitor) throughwhich the computer may receive input/provide output, for example to auser, operator or another computer or system (not shown). Input/outputdevices such as the display device, keyboard, the mouse, and other meansor mechanisms (e.g., touch screen interface) through which interactionwith the computer system may occur are generally known in the art, and adetailed discussion thereof is omitted here for convenience only andshould not be considered limiting. The computer includes a network portfor connecting the computer to an internal or external network, such as,for example the network. The computer is connected to a storage devicethat includes program instructions for software application(s) thatprovides the logical functions of the computer-implemented apparatusand/or method(s) of the present disclosure. The storage device alsocontains a database for storing data.

Those skilled in the art will recognize that the program instructionsfor software applications implementing all or a portion of one or moreembodiment(s) of the present disclosure may be written in a programminglanguage such as Java or C++, and that the database may be implementedwith a database package such as Microsoft Access™ database managementsystem (DBMS) such as Microsoft SQL Server™, Microsoft SQL Server CE™,IBM DB2™, mySQL or postgreSQL.

The embodiments of the present disclosure may be implemented with anycombination of hardware and software. If implemented as acomputer-implemented apparatus, the present disclosure is implementedusing means for performing all of the steps and functions describedabove.

The embodiments of the present disclosure can be included in an articleof manufacture (e.g., one or more computer program products) having, forinstance, computer useable or computer readable media. The media hasembodied therein, for instance, computer readable program code means,including computer-executable instructions, for providing andfacilitating the mechanisms of the embodiments of the presentdisclosure. The article of manufacture can be included as part of acomputer system or sold separately.

While specific embodiments have been described in detail in theforegoing detailed description and illustrated in the accompanyingdrawings, it will be appreciated by those skilled in the art thatvarious modifications and alternatives to those details could bedeveloped in light of the overall teachings of the disclosure and thebroad inventive concepts thereof. It is understood, therefore, that thescope of the present disclosure is not limited to the particularexamples and implementations disclosed herein, but is intended to covermodifications within the spirit and scope thereof as defined by theappended claims and any and all equivalents thereof.

What is claimed is:
 1. A microfluidic device comprising: two or moresubstrates bonded together to form a plurality of trapping devices, eachtrapping device comprising: a sample reservoir; an inlet channel influid communication with the sample reservoir; a plurality of trappingchannels in fluid communication with the inlet channel, each trappingchannel having a length, a width, and a height; and an exit channel influid communication with the plurality of trapping channels, wherein:the length of each trapping channel is measured in a direction from theinlet channel to the exit channel through the trapping channel, thewidth is measured in a direction orthogonal to the length direction andwithin a plane that is parallel to the surface of at least one of thesubstrates, and the height is measured in a direction that is orthogonalto the length and width directions, each trapping channel comprises aplurality of sections arranged end to end along the length of therespective trapping channel, wherein the widths of at least two adjacentsections vary with respect to each other, for at least one trappingchannel, the heights of at least two of the plurality of sections fortrapping a biological subject differ from each other such that theaspect ratio of the width to the height of the respective section iswithin a range of about 0.2 to about 2.0, and the exit channels of atleast two of the plurality of trapping devices are in fluidcommunication with one another via an intermediate exit channel.
 2. Themicrofluidic device of claim 1, wherein the plurality of sectionsincludes a first section, a second section, and a third section, whereinthe first section of the trapping channel is proximate to the inletchannel, the third section of the trapping channel is distal to theinlet channel, and the second section is positioned between the firstand third sections; and wherein the height of the first section isgreater than the height of the second section, and wherein the height ofthe second section is greater than the height of the third section. 3.The microfluidic device of claim 1, wherein the widths of the at leasttwo adjacent sections that vary in widths, and/or the heights of the atleast two sections that differ in height change gradually.
 4. Themicrofluidic device of claim 1, wherein a plurality of intermediate exitchannels joins in fluid communication with a final exit channel.
 5. Themicrofluidic device of claim 1, wherein the respective exit channels ofthe at least two trapping devices are sized such that a flow througheach exit channel experiences similar hydraulic resistance.
 6. Themicrofluidic device of claim 1, wherein each trapping device furthercomprises a micro-well having a substantially frustoconical shape,wherein the micro-well is in fluid communication with the samplereservoir such that biological subjects and reagents in the well areable to be deposited into the sample reservoir.
 7. The microfluidicdevice of claim 1, wherein a first end of the inlet channel adjacent thereservoir has a height of between about 1 μm and about 500 μm and awidth of between about 1 μm and about 750 μm, wherein the inlet channelconnects the plurality of the trapping channels.
 8. The microfluidicdevice of claim 7, wherein the length of each of the plurality oftrapping channels is between about 200 μm and about 6 mm.
 9. Themicrofluidic device of claim 1, wherein the geometry of each trappingchannel is configured to position a single biological subject in aspecific orientation.
 10. The microfluidic device of claim 9, whereinthe biological subject comprises a C. elegans worm.